6 papers
CDRL: Certification-Driven Reinforcement Learning for Neutrino Flavor Model Discovery
Piyush Jha, Jake Rudolph, Victoria Knapp-Pérez +3
Many scientific discovery problems require searching combinatorial hypothesis spaces under complex domain constraints. Reinforcement learning (RL) offers a promising approach, but…
Towards AI-assisted Neutrino Flavor Theory Design
Jason Benjamin Baretz, Max Fieg, Vijay Ganesh +4
Particle physics theories, such as those which explain neutrino flavor mixing, arise from a vast landscape of model-building possibilities. A model's construction typically relies…
INFLAVON: CMB as cosmic tracer of Flavor physics
Mu-Chun Chen, Anish Ghoshal, V. Knapp-Perez +3
We unify one of the most widely studied frameworks to explain the hierarchical structure of the flavor sector in the Standard Model, the Froggatt-Nielsen mechanism, with cosmic inf…
Demystifying stringy miracles with eclectic flavor symmetries
V. Knapp-Perez, Xiang-Gan Liu, Hans Peter Nilles +1
Effective field theories arising from string compactifications are subject to constraints originating from the duality transformations of string theory. Interpreting these so-calle…
Cosmological Stasis from Field-Dependent Decay
Fei Huang, V. Knapp-Perez
Cosmological stasis is a new type of epoch in the cosmological timeline during which the cosmological abundances of different energy components -- such as vacuum energy, matter, an…
Modular flavored dark matter
Alexander Baur, Mu-Chun Chen, V. Knapp-Perez +1
Discrete flavor symmetries have been an appealing approach for explaining the observed flavor structure, which is not justified in the Standard Model (SM). Typically, these models…